Interview-ready Resume Project | Real-Time Kafka Spark Streaming - Kappa -Data Engineering 1-3yrs

Prepare for Data Engineering Interviews (1–3 years experience) or looking to add a "real-time data engineering project for Resume", this video is for you along with " How this project should be written and explained for ATS screening and interviews. clearance"

We break down a production-grade Kappa Architecture using a real-time stock market data pipeline, designed with Kafka, Spark Structured Streaming, Delta Lake, CDC (Debezium), and Medallion Architecture.
This is not just architecture theory — the focus is on:
How recruiters evaluate real-time projects;
How ATS parses project descriptions ;
How interviewers cross-question streaming pipelines

Instead of theory, you’ll know
How to explain Real-Time Streaming architectures in interviews,
Including why Kappa architecture is preferred over Lambda for low-latency systems.

🔹 What you’ll learn:
Kappa Architecture explained using a real-time stock market data pipeline,
Kafka ingestion at High Throughput event streams (120K+ events/sec)
CDC-based enrichment using Debezium
Spark Structured Streaming internals (micro-batching, state, checkpoints)
Exactly-once processing using idempotent MERGE into Delta Lake
Failure handling using checkpointing and replay
Applying Medallion Architecture (Bronze / Silver / Gold) in streaming pipelines
Why Airflow is used for orchestration in streaming systems
How to write this project in your resume (ATS-friendly)

🔹 Who should watch:
Career switchers moving into Data Engineering
Data Analysts with 1–3 years of experience
Data Engineers with 1–3 years of experience
Candidates preparing for Kafka, Spark, and streaming interviews
Anyone looking for real-time data engineering projects for resume

Our Website - https://versiontwo.tg117.in/

Contact us via Call/Whatsapp - +91 9684000938
Email : tg117official@gmail.com

To know about Training on Full stack courses in Data Engg and Career support.
Google Forms : https://forms.gle/BFRskqhD3GVNSV5U6 -- To Receive a Call Back from Us

The Data Engineering ecosystem consists of..- Azure Data Factory, DataBricks, AWS EMR, Glue, Lambda, Apache Airflow, NiFi, MongoDB. Spark-Streaming, Python Programming, Apache Hadoop, Apache Hive, PySpark, SparkSQL, Kafka, Github, etc.

#KappaArchitecture #DataEngineeringProject #ATSOptimizedResume #RealTimeDataEngineering
#KafkaSpark #DataEngineeringInterview #StreamingData #CareerSwitchToDataEngineering #SparkStructuredStreaming #KappaArchitecture #DataEngineeringProject #ATSOptimizedResume #RealTimeDataEngineering #KafkaSpark #DataEngineeringInterview #StreamingData
#CareerSwitchToDataEngineering #SparkStructuredStreaming #BigDataCareers